Speed Density vs MAF

robert dingli r.dingli at ee.mu.OZ.AU
Fri Nov 17 05:56:54 GMT 1995


Mike Klopfer writes
> 
> After looking at some articles on engine modeling I'm wondering how
> much is gained by either MAP or MAF. The primary input variables to the
> system would seem to be throttle position, injection time and rpm (and 
> time and ambient pressure, humidity?). Given a sufficiently good model 
> of the
> engine this should be enough to calculate the amount of air entering
> the cylinders. Since airflow or manifold pressure are effect of these
> inputs it would seem that these would provide quicker response to
> transients. The main question I suppose is how difficult is it to
> accurately calculate the number of moles entering the cylinder from 
> these inputs. One paper as I recall got a good prediction using a lookup
> table indexed by throttle angle and rpm. 

In the steady state, throttle position and rpm are generally sufficient
to estimate airflow relatively accurately for manifold pressures away from
atmospheric.  This is certainly the system used on many open-loop 
EFI systems, especially in racing.  Transient behaviour is lumped together
in something resembling a first order PD response and while everything is
running rich then at least the engine is happy.

The Australian Ford Falcon (EECV) uses a speed density (throttle) system
rather than a MAF measurement.  As far as I know, they intend on using
the system well into the future.  The EECV uses quite a complex internal
model for state estimation.

The basis behind on-line modelling is to determine parameters which are
either not measurable accurately or are delayed due to transportation or
sensor delays.  There is a causality problem when using sensor data
of measurements of events that occurred a number of cycles beforehand.
This data is fed into a parameter estimator which updates an interal
model of the process.  The model's estimates of airflow, fuel puddle mass,
intake to AFR sensor delay etc. are used to calculate the current fuelling
parameters.  The implementation of such systems differs between researchers.
For further reading try SAE# 930766, 930857, 920290, 930767 ...

Robert Dingli
-- 
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             Robert Dingli           r.dingli at ee.mu.oz.au

Power and Control Systems                 Thermodynamics Research Lab
Electrical Engineering                    Mechanical Engineering
   (+613) 9344 7966                          (+613) 9344 6728
  University of Melbourne, Parkville, 3052, Victoria, AUSTRALIA
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